diff --git a/econml/tests/test_cate_interpreter.py b/econml/tests/test_cate_interpreter.py
index eff4393cc..8aa359087 100644
--- a/econml/tests/test_cate_interpreter.py
+++ b/econml/tests/test_cate_interpreter.py
@@ -4,7 +4,6 @@
 import numpy as np
 import unittest
 import pytest
-import matplotlib
 from econml.cate_interpreter import SingleTreeCateInterpreter, SingleTreePolicyInterpreter
 from econml.dml import LinearDML
 from sklearn.linear_model import LinearRegression, LogisticRegression
@@ -14,11 +13,11 @@
     from graphviz import Graph
     g = Graph()
     g.render()
+    import matplotlib
+    matplotlib.use('Agg')
 except Exception:
     graphviz_works = False
 
-matplotlib.use('Agg')
-
 
 @pytest.mark.skipif(not graphviz_works, reason="graphviz must be installed to run CATE interpreter tests")
 class TestCateInterpreter(unittest.TestCase):
diff --git a/econml/tests/test_dowhy.py b/econml/tests/test_dowhy.py
index 7208e8057..4d7c37ddf 100644
--- a/econml/tests/test_dowhy.py
+++ b/econml/tests/test_dowhy.py
@@ -62,6 +62,11 @@ def clf():
                 else:
                     est_dowhy = est.dowhy.fit(Y, T, X=X, W=W)
                 # test causal graph
+                # need to set matplotlib backend before viewing model
+
+                import matplotlib
+                matplotlib.use('Agg')
+
                 est_dowhy.view_model(layout=None)
                 # test refutation estimate
                 est_dowhy.refute_estimate(method_name="random_common_cause", num_simulations=3)
diff --git a/econml/tests/test_shap.py b/econml/tests/test_shap.py
index fecbb202c..0761d565b 100644
--- a/econml/tests/test_shap.py
+++ b/econml/tests/test_shap.py
@@ -125,6 +125,8 @@ def test_discrete_t(self):
 
     def test_identical_output(self):
         # import here since otherwise test collection would fail if matplotlib is not installed
+        import matplotlib
+        matplotlib.use('Agg')
         from shap.plots import scatter, heatmap, bar, beeswarm, waterfall
 
         # Treatment effect function